Abstract: The technologies described herein are generally directed to facilitating operation of system that can include a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. In embodiments, the operations can include receiving, from a source user equipment, a first request to communicate to a destination group of user equipment via a multi-cast connection. Further operations can include identifying respective service areas of ones of the destination group, comprising a service area of a destination user equipment of the destination group. In some embodiments, operations can include generating a second request to initiate the multi-cast connection, the second request comprising the destination group of user equipment with the respective service areas, wherein the respective service area of the destination user equipment is for selection, by second network equipment based on the service area, a gateway group of base station equipment.

Abstract: The technologies described herein are generally directed to facilitating operation of system that can include a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. In embodiments, the operations can include receiving, from a source user equipment, a first request to communicate to a destination group of user equipment via a multi-cast connection. Further operations can include identifying respective service areas of ones of the destination group, comprising a service area of a destination user equipment of the destination group. In some embodiments, operations can include generating a second request to initiate the multi-cast connection, the second request comprising the destination group of user equipment with the respective service areas, wherein the respective service area of the destination user equipment is for selection, by second network equipment based on the service area, a gateway group of base station equipment.

Abstract: A connected-device network can continually learn from abstract sensory data (e.g., speech processing, cognitive inference, and/or computer vision image segmentation) and can generate never-seen-before data in real time. In one aspect, the network devices extract important correlations in the sensor data based on network data collected at different time slice and/or locations. Further, underlying relationships in a set of data can be detected as the sensor data transverses through different layers of the network. Moreover, the network devices can provide logic in different layers to help classify the sensor data early in the detection process (e.g., instead of waiting for it to reach its final destination).

Abstract: A connected-device network can continually learn from abstract sensory data (e.g., speech processing, cognitive inference, and/or computer vision image segmentation) and can generate never-seen-before data in real time. In one aspect, the network devices extract important correlations in the sensor data based on network data collected at different time slice and/or locations. Further, underlying relationships in a set of data can be detected as the sensor data transverses through different layers of the network. Moreover, the network devices can provide logic in different layers to help classify the sensor data early in the detection process (e.g., instead of waiting for it to reach its final destination).

Abstract: Aspects of the subject disclosure may include, for example, selection of network functions in a communication network based on dynamic load and/or location of the network functions. A network repository function may subscribe to receive dynamic load information of network functions and then use the dynamic load information when selecting network functions. The network repository function may also determine a distance between network functions and then use the distance when selecting network functions. Other embodiments are disclosed.

Abstract: The technologies described herein are generally directed to facilitating operation of system that can include a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. In embodiments, the operations can include receiving, from a source user equipment, a first request to communicate to a destination group of user equipment via a multi-cast connection. Further operations can include identifying respective service areas of ones of the destination group, comprising a service area of a destination user equipment of the destination group. In some embodiments, operations can include generating a second request to initiate the multi-cast connection, the second request comprising the destination group of user equipment with the respective service areas, wherein the respective service area of the destination user equipment is for selection, by second network equipment based on the service area, a gateway group of base station equipment.

Abstract: A connected-device network can continually learn from abstract sensory data (e.g., speech processing, cognitive inference, and/or computer vision image segmentation) and can generate never-seen-before data in real time. In one aspect, the network devices extract important correlations in the sensor data based on network data collected at different time slice and/or locations. Further, underlying relationships in a set of data can be detected as the sensor data transverses through different layers of the network. Moreover, the network devices can provide logic in different layers to help classify the sensor data early in the detection process (e.g., instead of waiting for it to reach its final destination).